Bio-Medical Materials and Engineering 23 (2013) 513–531 DOI 10.3233/BME-130773 IOS Press
513
Discrimination of Parkinsonian tremor from essential tremor using statistical signal characterization of the spectrum of accelerometer signal A. Hossen a,∗ , M. Muthuraman b , Z. Al-Hakim a , J. Raethjen c , G. Deuschl c and U. Heute b a
Department of Electrical and Computer Engineering, Sultan Qaboos University, Muscat, Oman Institute for Circuit and System Theory, Faculty of Engineering, University of Kiel, Kiel, Germany c Department of Neurology, University of Kiel, Kiel, Germany b
Received 20 February 2013 Accepted 2 July 2013 Abstract. A new technique for discrimination of Parkinson tremor from essential tremor is presented in this paper. This technique is based on Statistical Signal Characterization (SSC) of the spectrum of the accelerometer signal. The data has been recorded for diagnostic purposes in the Department of Neurology of the University of Kiel, Germany. Two sets of data are used. The training set, which consists of 21 essential-tremor (ET) subjects and 19 Parkinson-disease (PD) subjects, is used to obtain the threshold value of the classification factor differentiating between the two subjects. The test data set, which consists of 20 ET and 20 PD subjects, is used to test the technique and evaluate its performance. Three of twelve newly derived SSC parameters show good discrimination results. Specific results of those three parameters on training data and test data are shown in detail. A linear combination of the effects of those parameters on the discrimination results is also included. A total discrimination accuracy of 90% is obtained. Keywords: Statistical signal characterization, FFT spectrum, Parkinson tremor, essential tremor, accelerometer signals, discrimination
1. Introduction The available clinical diagnostic methods exhibit difficulties in discriminating between Essential tremor (ET) and the tremor in Parkinson’s disease (PD) [1]. The differentiation between the two tremors is more difficult at early stages of the diseases, when, however, a specific treatment would be especially important. The reason is the fact that ET is a relatively benign disease with the tremor being the main symptom, while PD is a progressive neuro-degenerative disorder in the course of which other disabling neurological deficits develop [2,3]. In those unclear cases, dopamine-transporter imaging is used which *
Address for correspondence: A. Hossen, Department of Electrical and Computer Engineering, Sultan Qaboos University, P.O. Box 33, Al-Khoud, 123 Muscat, Oman. E-mail: [email protected]. 0959-2989/13/$27.50 © 2013 – IOS Press and the authors. All rights reserved
513
Discrimination of Parkinsonian tremor from essential tremor using statistical signal characterization of the spectrum of accelerometer signal A. Hossen a,∗ , M. Muthuraman b , Z. Al-Hakim a , J. Raethjen c , G. Deuschl c and U. Heute b a
Department of Electrical and Computer Engineering, Sultan Qaboos University, Muscat, Oman Institute for Circuit and System Theory, Faculty of Engineering, University of Kiel, Kiel, Germany c Department of Neurology, University of Kiel, Kiel, Germany b
Received 20 February 2013 Accepted 2 July 2013 Abstract. A new technique for discrimination of Parkinson tremor from essential tremor is presented in this paper. This technique is based on Statistical Signal Characterization (SSC) of the spectrum of the accelerometer signal. The data has been recorded for diagnostic purposes in the Department of Neurology of the University of Kiel, Germany. Two sets of data are used. The training set, which consists of 21 essential-tremor (ET) subjects and 19 Parkinson-disease (PD) subjects, is used to obtain the threshold value of the classification factor differentiating between the two subjects. The test data set, which consists of 20 ET and 20 PD subjects, is used to test the technique and evaluate its performance. Three of twelve newly derived SSC parameters show good discrimination results. Specific results of those three parameters on training data and test data are shown in detail. A linear combination of the effects of those parameters on the discrimination results is also included. A total discrimination accuracy of 90% is obtained. Keywords: Statistical signal characterization, FFT spectrum, Parkinson tremor, essential tremor, accelerometer signals, discrimination
1. Introduction The available clinical diagnostic methods exhibit difficulties in discriminating between Essential tremor (ET) and the tremor in Parkinson’s disease (PD) [1]. The differentiation between the two tremors is more difficult at early stages of the diseases, when, however, a specific treatment would be especially important. The reason is the fact that ET is a relatively benign disease with the tremor being the main symptom, while PD is a progressive neuro-degenerative disorder in the course of which other disabling neurological deficits develop [2,3]. In those unclear cases, dopamine-transporter imaging is used which *
Address for correspondence: A. Hossen, Department of Electrical and Computer Engineering, Sultan Qaboos University, P.O. Box 33, Al-Khoud, 123 Muscat, Oman. E-mail: [email protected]. 0959-2989/13/$27.50 © 2013 – IOS Press and the authors. All rights reserved
